#Subsample of metrics from MHSDS data
CAMHS_data <- MHSDS_main_pooled_dashboard %>%
filter(PRIMARY_LEVEL_DESCRIPTION=="England",
MEASURE_ID %in% c("CYP01","MHS61a","CYP23","MHS30d","MHS32a")) %>%
filter(.,!(MEASURE_ID=="MHS32a"&BREAKDOWN!="England")) %>%
mutate(MEASURE_KEY=case_when(
MEASURE_ID=="MHS30d" ~ "Attended contacts (<18)",
MEASURE_ID=="CYP01" ~ "People in contact",
MEASURE_ID=="MHS61a" ~ "First contacts (<18)",
MEASURE_ID=="CYP23" ~ "Open referrals",
MEASURE_ID=="MHS32a" ~ "New referrals (<18)",
TRUE ~ "NA"
)) %>%
select(.,start_date,end_date,month_year,PRIMARY_LEVEL_DESCRIPTION,MEASURE_ID,MEASURE_KEY,MEASURE_VALUE) %>%
mutate(.,MEASURE_VALUE=as.numeric(MEASURE_VALUE),
timing=ifelse(start_date<ymd("2020-04-01"),"Pre-COVID","Post-COVID")) %>%
mutate(.,timing=fct_relevel(timing, c("Pre-COVID","Post-COVID"))) %>%
arrange(.,start_date) %>%
as_tibble()
#Percentage change compared to a year ago
#For example, for March 2020 show the % change between March 2019 and March 2020
CAMHS_yearly_changes <- CAMHS_data %>%
select(.,PRIMARY_LEVEL_DESCRIPTION,MEASURE_ID,MEASURE_KEY,MEASURE_VALUE,start_date,month_year,timing) %>%
mutate(start_date=lubridate::ymd(start_date)) %>%
mutate(.,start_date_l1=start_date-years(1)) #Adds a new column with the month a year before
#Auxiliary dataset with data points from a year before
CAMHS_data_l1 <- CAMHS_yearly_changes %>%
select(.,start_date,MEASURE_VALUE,PRIMARY_LEVEL_DESCRIPTION,MEASURE_ID,MEASURE_KEY) %>%
rename(.,MEASURE_VALUE_l1=MEASURE_VALUE,start_date_l1=start_date)
#Merge auxiliary data back in
CAMHS_yearly_changes <- left_join(CAMHS_yearly_changes,
CAMHS_data_l1,
by=c("start_date_l1","PRIMARY_LEVEL_DESCRIPTION","MEASURE_ID","MEASURE_KEY")) %>%
arrange(.,MEASURE_ID,start_date) %>%
mutate(pct_change_l1=(MEASURE_VALUE-MEASURE_VALUE_l1)/MEASURE_VALUE_l1*100) %>%
filter(.,!is.na(pct_change_l1))
rm(CAMHS_data_l1)
People in contact with CAMHS
- Measure code: CYP01
- Measure description: People in contact with children and young people’s mental health services at the end of the reporting period
- Source: NHS England, Monthly MHSDS Statistics, Metadata
Raw time series
#Data
CAMHS_data_cyp01 <- CAMHS_data %>%
filter(.,MEASURE_ID=="CYP01")
CAMHS_reldata_cyp01 <- CAMHS_yearly_changes %>%
filter(.,MEASURE_ID=="CYP01")
#Time series chart
CAMHS_raw_chart_cyp01 <- CAMHS_data_cyp01 %>%
ggplot(., aes(x=start_date, y=MEASURE_VALUE, group= MEASURE_KEY)) +
geom_line(aes(color= MEASURE_KEY),
size=1) +
scale_x_date(date_labels = "%b %Y",date_breaks = "3 months") +
scale_y_continuous(labels = scales::comma) +
facet_wrap(~timing, scales = "free_x") +
theme_ipsum() +
xlab("") +
ylab("") +
labs(col="") +
scale_color_brewer(palette = "Set1") +
theme(legend.position="bottom",
panel.border = element_blank(),
strip.text = element_text(size=8),
text = element_text(size = 8),
legend.title=element_text(size=8),
legend.text=element_text(size=8),
axis.text = element_text(size = 8),
axis.text.y = element_text(size = 8),
axis.text.x = element_text(angle = 45, hjust = 1,size = 8),
axis.title.x = element_text(margin = unit(c(3, 0, 0, 0), "mm"),size = 8),
axis.title.y = element_text(size = 8))
ggplotly(CAMHS_raw_chart_cyp01)
#Underlying data
CAMHS_data_cyp01 %>%
select(.,start_date,MEASURE_KEY,MEASURE_VALUE) %>%
arrange(.,start_date) %>%
knitr::kable(., align = "lccrr",format.args = list(big.mark = ","))
| 2018-05-01 |
People in contact |
222,156 |
| 2018-06-01 |
People in contact |
225,407 |
| 2018-07-01 |
People in contact |
218,557 |
| 2018-08-01 |
People in contact |
213,702 |
| 2018-09-01 |
People in contact |
218,764 |
| 2018-10-01 |
People in contact |
227,845 |
| 2018-11-01 |
People in contact |
223,744 |
| 2018-12-01 |
People in contact |
227,679 |
| 2019-01-01 |
People in contact |
229,217 |
| 2019-02-01 |
People in contact |
233,831 |
| 2019-03-01 |
People in contact |
241,926 |
| 2019-04-01 |
People in contact |
218,678 |
| 2019-05-01 |
People in contact |
230,443 |
| 2019-06-01 |
People in contact |
225,480 |
| 2019-07-01 |
People in contact |
226,647 |
| 2019-08-01 |
People in contact |
218,826 |
| 2019-09-01 |
People in contact |
221,428 |
| 2019-10-01 |
People in contact |
225,507 |
| 2019-11-01 |
People in contact |
230,739 |
| 2019-12-01 |
People in contact |
231,056 |
| 2020-01-01 |
People in contact |
236,396 |
| 2020-02-01 |
People in contact |
240,401 |
| 2020-03-01 |
People in contact |
237,088 |
| 2020-04-01 |
People in contact |
281,199 |
| 2020-05-01 |
People in contact |
273,706 |
| 2020-06-01 |
People in contact |
272,529 |
| 2020-07-01 |
People in contact |
275,439 |
| 2020-08-01 |
People in contact |
271,462 |
| 2020-09-01 |
People in contact |
286,880 |
| 2020-10-01 |
People in contact |
296,414 |
| 2020-11-01 |
People in contact |
309,311 |
| 2020-12-01 |
People in contact |
311,119 |
| 2021-01-01 |
People in contact |
307,335 |
| 2021-02-01 |
People in contact |
306,997 |
| 2021-03-01 |
People in contact |
317,845 |
| 2021-04-01 |
People in contact |
323,240 |
| 2021-05-01 |
People in contact |
337,426 |
| 2021-06-01 |
People in contact |
340,694 |
| 2021-07-01 |
People in contact |
342,565 |
| 2021-08-01 |
People in contact |
331,912 |
| 2021-09-01 |
People in contact |
337,080 |
Monthly average, per year
#Average per calendar year
CAMHS_data_cyp01 %>%
mutate(.,year=lubridate::year(start_date)) %>%
group_by(MEASURE_ID,MEASURE_KEY,year) %>%
summarise(average=mean(MEASURE_VALUE,na.rm = TRUE),
months_included= n()) %>%
ungroup() %>%
filter(.,months_included==12) %>%
knitr::kable(., align = "lccrr")
| CYP01 |
People in contact |
2019 |
227814.8 |
12 |
| CYP01 |
People in contact |
2020 |
274328.7 |
12 |
Relative changes compared to last year
#Relative changes chart
CAMHS_changes_chart_cyp01 <- CAMHS_reldata_cyp01 %>%
ggplot(., aes(x=start_date, y=pct_change_l1, group= MEASURE_KEY)) +
facet_wrap(~timing, scales = "free_x") +
geom_line(aes(color= MEASURE_KEY),size=1) +
geom_hline(yintercept=0, linetype="dashed", color = "red") +
scale_x_date(date_labels = "%b %Y",date_breaks = "1 month") +
theme_ipsum() +
xlab("") +
ylab("% change") +
labs(col="") +
scale_color_manual(values=c("Open referrals" = "aquamarine4",
"People in contact" = "tomato3",
"First contactsn (<18)" = "olivedrab4",
"Attended contacts (<18)" = "violetred",
"New referrals (<18)" = "magenta1")) +
theme(legend.position="bottom",
panel.border = element_blank(),
strip.text = element_text(size=8),
text = element_text(size = 8),
legend.title=element_text(size=8),
legend.text=element_text(size=8),
axis.text = element_text(size = 8),
axis.text.y = element_text(size = 8),
axis.text.x = element_text(angle = 45, hjust = 1,size = 8),
axis.title.x = element_text(margin = unit(c(3, 0, 0, 0), "mm"),size = 8),
axis.title.y = element_text(size = 8))
ggplotly(CAMHS_changes_chart_cyp01)
#Underlying data
CAMHS_reldata_cyp01 %>%
select(.,start_date,MEASURE_KEY,pct_change_l1) %>%
arrange(.,start_date) %>%
knitr::kable(., align = "lccrr",format.args = list(big.mark = ","))
| 2019-05-01 |
People in contact |
3.7302616 |
| 2019-06-01 |
People in contact |
0.0323859 |
| 2019-07-01 |
People in contact |
3.7015515 |
| 2019-08-01 |
People in contact |
2.3977314 |
| 2019-09-01 |
People in contact |
1.2177506 |
| 2019-10-01 |
People in contact |
-1.0261362 |
| 2019-11-01 |
People in contact |
3.1263408 |
| 2019-12-01 |
People in contact |
1.4832286 |
| 2020-01-01 |
People in contact |
3.1319667 |
| 2020-02-01 |
People in contact |
2.8097216 |
| 2020-03-01 |
People in contact |
-1.9997851 |
| 2020-04-01 |
People in contact |
28.5904389 |
| 2020-05-01 |
People in contact |
18.7738400 |
| 2020-06-01 |
People in contact |
20.8661522 |
| 2020-07-01 |
People in contact |
21.5277502 |
| 2020-08-01 |
People in contact |
24.0538144 |
| 2020-09-01 |
People in contact |
29.5590440 |
| 2020-10-01 |
People in contact |
31.4433698 |
| 2020-11-01 |
People in contact |
34.0523275 |
| 2020-12-01 |
People in contact |
34.6509071 |
| 2021-01-01 |
People in contact |
30.0085450 |
| 2021-02-01 |
People in contact |
27.7020478 |
| 2021-03-01 |
People in contact |
34.0620360 |
| 2021-04-01 |
People in contact |
14.9506222 |
| 2021-05-01 |
People in contact |
23.2804542 |
| 2021-06-01 |
People in contact |
25.0120171 |
| 2021-07-01 |
People in contact |
24.3705503 |
| 2021-08-01 |
People in contact |
22.2683101 |
| 2021-09-01 |
People in contact |
17.4986057 |
New referrals (<18)
- Measure code: MHS32a
- Measure description: Referrals starting in RP, aged 0-18
- Source: NHS England, Monthly MHSDS Statistics, Metadata
Raw time series
#Data
CAMHS_data_cyp32a <- CAMHS_data %>%
filter(.,MEASURE_ID=="MHS32a")
CAMHS_reldata_cyp32a <- CAMHS_yearly_changes %>%
filter(.,MEASURE_ID=="MHS32a")
#Time series chart
CAMHS_raw_chart_cyp32a <- CAMHS_data_cyp32a %>%
ggplot(., aes(x=start_date, y=MEASURE_VALUE, group= MEASURE_KEY)) +
geom_line(aes(color= MEASURE_KEY),
size=1) +
scale_x_date(date_labels = "%b %Y",date_breaks = "3 months") +
scale_y_continuous(labels = scales::comma) +
facet_wrap(~timing, scales = "free_x") +
theme_ipsum() +
xlab("") +
ylab("") +
labs(col="") +
scale_color_brewer(palette = "Set1") +
theme(legend.position="bottom",
panel.border = element_blank(),
strip.text = element_text(size=8),
text = element_text(size = 8),
legend.title=element_text(size=8),
legend.text=element_text(size=8),
axis.text = element_text(size = 8),
axis.text.y = element_text(size = 8),
axis.text.x = element_text(angle = 45, hjust = 1,size = 8),
axis.title.x = element_text(margin = unit(c(3, 0, 0, 0), "mm"),size = 8),
axis.title.y = element_text(size = 8))
ggplotly(CAMHS_raw_chart_cyp32a)
#Underlying data
CAMHS_data_cyp32a %>%
select(.,start_date,MEASURE_KEY,MEASURE_VALUE) %>%
arrange(.,start_date) %>%
knitr::kable(., align = "lccrr",format.args = list(big.mark = ","))
| 2019-04-01 |
New referrals (<18) |
64,095 |
| 2019-05-01 |
New referrals (<18) |
71,119 |
| 2019-06-01 |
New referrals (<18) |
67,449 |
| 2019-07-01 |
New referrals (<18) |
71,743 |
| 2019-08-01 |
New referrals (<18) |
46,403 |
| 2019-09-01 |
New referrals (<18) |
64,284 |
| 2019-10-01 |
New referrals (<18) |
83,290 |
| 2019-11-01 |
New referrals (<18) |
79,100 |
| 2019-12-01 |
New referrals (<18) |
65,547 |
| 2020-01-01 |
New referrals (<18) |
84,624 |
| 2020-02-01 |
New referrals (<18) |
80,555 |
| 2020-03-01 |
New referrals (<18) |
72,532 |
| 2020-04-01 |
New referrals (<18) |
41,411 |
| 2020-05-01 |
New referrals (<18) |
46,262 |
| 2020-06-01 |
New referrals (<18) |
60,370 |
| 2020-07-01 |
New referrals (<18) |
67,967 |
| 2020-08-01 |
New referrals (<18) |
51,357 |
| 2020-09-01 |
New referrals (<18) |
75,222 |
| 2020-10-01 |
New referrals (<18) |
88,523 |
| 2020-11-01 |
New referrals (<18) |
92,228 |
| 2020-12-01 |
New referrals (<18) |
75,841 |
| 2021-01-01 |
New referrals (<18) |
68,149 |
| 2021-02-01 |
New referrals (<18) |
70,169 |
| 2021-03-01 |
New referrals (<18) |
98,112 |
| 2021-04-01 |
New referrals (<18) |
85,598 |
| 2021-05-01 |
New referrals (<18) |
101,421 |
| 2021-06-01 |
New referrals (<18) |
98,037 |
| 2021-07-01 |
New referrals (<18) |
85,801 |
| 2021-08-01 |
New referrals (<18) |
57,289 |
| 2021-09-01 |
New referrals (<18) |
84,264 |
Monthly average, per year
#Average per calendar year
CAMHS_data_cyp32a %>%
mutate(.,year=lubridate::year(start_date)) %>%
group_by(MEASURE_ID,MEASURE_KEY,year) %>%
summarise(average=mean(MEASURE_VALUE,na.rm = TRUE),
months_included= n()) %>%
ungroup() %>%
filter(.,months_included==12) %>%
knitr::kable(., align = "lccrr")
| MHS32a |
New referrals (<18) |
2020 |
69741 |
12 |
Relative changes compared to last year
#Relative changes chart
CAMHS_changes_chart_cyp32a <- CAMHS_reldata_cyp32a %>%
ggplot(., aes(x=start_date, y=pct_change_l1, group= MEASURE_KEY)) +
facet_wrap(~timing, scales = "free_x") +
geom_line(aes(color= MEASURE_KEY),size=1) +
geom_hline(yintercept=0, linetype="dashed", color = "red") +
scale_x_date(date_labels = "%b %Y",date_breaks = "1 month") +
theme_ipsum() +
xlab("") +
ylab("% change") +
labs(col="") +
scale_color_manual(values=c("Open referrals" = "aquamarine4",
"People in contact" = "tomato3",
"First contacts (<18)" = "olivedrab4",
"Attended contacts (<18)" = "violetred",
"New referrals (<18)" = "magenta1")) +
theme(legend.position="bottom",
panel.border = element_blank(),
strip.text = element_text(size=8),
text = element_text(size = 8),
legend.title=element_text(size=8),
legend.text=element_text(size=8),
axis.text = element_text(size = 8),
axis.text.y = element_text(size = 8),
axis.text.x = element_text(angle = 45, hjust = 1,size = 8),
axis.title.x = element_text(margin = unit(c(3, 0, 0, 0), "mm"),size = 8),
axis.title.y = element_text(size = 8))
ggplotly(CAMHS_changes_chart_cyp32a)
#Underlying data
CAMHS_reldata_cyp32a %>%
select(.,start_date,MEASURE_KEY,pct_change_l1) %>%
arrange(.,start_date) %>%
knitr::kable(., align = "lccrr",format.args = list(big.mark = ","))
| 2020-04-01 |
New referrals (<18) |
-35.391216 |
| 2020-05-01 |
New referrals (<18) |
-34.951279 |
| 2020-06-01 |
New referrals (<18) |
-10.495337 |
| 2020-07-01 |
New referrals (<18) |
-5.263231 |
| 2020-08-01 |
New referrals (<18) |
10.676034 |
| 2020-09-01 |
New referrals (<18) |
17.015120 |
| 2020-10-01 |
New referrals (<18) |
6.282867 |
| 2020-11-01 |
New referrals (<18) |
16.596713 |
| 2020-12-01 |
New referrals (<18) |
15.704762 |
| 2021-01-01 |
New referrals (<18) |
-19.468472 |
| 2021-02-01 |
New referrals (<18) |
-12.893054 |
| 2021-03-01 |
New referrals (<18) |
35.267192 |
| 2021-04-01 |
New referrals (<18) |
106.703533 |
| 2021-05-01 |
New referrals (<18) |
119.231767 |
| 2021-06-01 |
New referrals (<18) |
62.393573 |
| 2021-07-01 |
New referrals (<18) |
26.239204 |
| 2021-08-01 |
New referrals (<18) |
11.550519 |
| 2021-09-01 |
New referrals (<18) |
12.020420 |
First contacts (<18)
- Measure code: MHS61a
- Measure description: First attended contacts for referrals open in the RP, aged 0-18
- Source: NHS England, Monthly MHSDS Statistics, Metadata
Raw time series
#Data
CAMHS_data_cyp61a <- CAMHS_data %>%
filter(.,MEASURE_ID=="MHS61a")
CAMHS_reldata_cyp61a <- CAMHS_yearly_changes %>%
filter(.,MEASURE_ID=="MHS61a")
#Time series chart
CAMHS_raw_chart_cyp61a <- CAMHS_data_cyp61a %>%
ggplot(., aes(x=start_date, y=MEASURE_VALUE, group= MEASURE_KEY)) +
geom_line(aes(color= MEASURE_KEY),
size=1) +
scale_x_date(date_labels = "%b %Y",date_breaks = "3 months") +
scale_y_continuous(labels = scales::comma) +
facet_wrap(~timing, scales = "free_x") +
theme_ipsum() +
xlab("") +
ylab("") +
labs(col="") +
scale_color_brewer(palette = "Set1") +
theme(legend.position="bottom",
panel.border = element_blank(),
strip.text = element_text(size=8),
text = element_text(size = 8),
legend.title=element_text(size=8),
legend.text=element_text(size=8),
axis.text = element_text(size = 8),
axis.text.y = element_text(size = 8),
axis.text.x = element_text(angle = 45, hjust = 1,size = 8),
axis.title.x = element_text(margin = unit(c(3, 0, 0, 0), "mm"),size = 8),
axis.title.y = element_text(size = 8))
ggplotly(CAMHS_raw_chart_cyp61a)
#Underlying data
CAMHS_data_cyp61a %>%
select(.,start_date,MEASURE_KEY,MEASURE_VALUE) %>%
arrange(.,start_date) %>%
knitr::kable(., align = "lccrr",format.args = list(big.mark = ","))
| 2019-04-01 |
First contacts (<18) |
51,694 |
| 2019-05-01 |
First contacts (<18) |
49,335 |
| 2019-06-01 |
First contacts (<18) |
47,035 |
| 2019-07-01 |
First contacts (<18) |
48,293 |
| 2019-08-01 |
First contacts (<18) |
36,352 |
| 2019-09-01 |
First contacts (<18) |
45,982 |
| 2019-10-01 |
First contacts (<18) |
54,568 |
| 2019-11-01 |
First contacts (<18) |
54,309 |
| 2019-12-01 |
First contacts (<18) |
41,945 |
| 2020-01-01 |
First contacts (<18) |
56,823 |
| 2020-02-01 |
First contacts (<18) |
52,305 |
| 2020-03-01 |
First contacts (<18) |
51,555 |
| 2020-04-01 |
First contacts (<18) |
43,246 |
| 2020-05-01 |
First contacts (<18) |
38,816 |
| 2020-06-01 |
First contacts (<18) |
46,559 |
| 2020-07-01 |
First contacts (<18) |
47,685 |
| 2020-08-01 |
First contacts (<18) |
39,035 |
| 2020-09-01 |
First contacts (<18) |
49,839 |
| 2020-10-01 |
First contacts (<18) |
56,951 |
| 2020-11-01 |
First contacts (<18) |
60,651 |
| 2020-12-01 |
First contacts (<18) |
49,468 |
| 2021-01-01 |
First contacts (<18) |
50,832 |
| 2021-02-01 |
First contacts (<18) |
48,337 |
| 2021-03-01 |
First contacts (<18) |
59,245 |
| 2021-04-01 |
First contacts (<18) |
57,734 |
| 2021-05-01 |
First contacts (<18) |
62,337 |
| 2021-06-01 |
First contacts (<18) |
63,397 |
| 2021-07-01 |
First contacts (<18) |
55,473 |
| 2021-08-01 |
First contacts (<18) |
43,083 |
| 2021-09-01 |
First contacts (<18) |
56,285 |
Monthly average, per year
#Average per calendar year
CAMHS_data_cyp61a %>%
mutate(.,year=lubridate::year(start_date)) %>%
group_by(MEASURE_ID,MEASURE_KEY,year) %>%
summarise(average=mean(MEASURE_VALUE,na.rm = TRUE),
months_included= n()) %>%
ungroup() %>%
filter(.,months_included==12) %>%
knitr::kable(., align = "lccrr")
| MHS61a |
First contacts (<18) |
2020 |
49411.08 |
12 |
Relative changes compared to last year
#Relative changes chart
CAMHS_changes_chart_cyp61a <- CAMHS_reldata_cyp61a %>%
ggplot(., aes(x=start_date, y=pct_change_l1, group= MEASURE_KEY)) +
facet_wrap(~timing, scales = "free_x") +
geom_line(aes(color= MEASURE_KEY),size=1) +
geom_hline(yintercept=0, linetype="dashed", color = "red") +
scale_x_date(date_labels = "%b %Y",date_breaks = "1 month") +
theme_ipsum() +
xlab("") +
ylab("% change") +
labs(col="") +
scale_color_manual(values=c("Open referrals" = "aquamarine4",
"People in contact" = "tomato3",
"First contacts (<18)" = "olivedrab4",
"Attended contacts (<18)" = "violetred",
"New referrals (<18)" = "magenta1")) +
theme(legend.position="bottom",
panel.border = element_blank(),
strip.text = element_text(size=8),
text = element_text(size = 8),
legend.title=element_text(size=8),
legend.text=element_text(size=8),
axis.text = element_text(size = 8),
axis.text.y = element_text(size = 8),
axis.text.x = element_text(angle = 45, hjust = 1,size = 8),
axis.title.x = element_text(margin = unit(c(3, 0, 0, 0), "mm"),size = 8),
axis.title.y = element_text(size = 8))
ggplotly(CAMHS_changes_chart_cyp61a)
#Underlying data
CAMHS_reldata_cyp61a %>%
select(.,start_date,MEASURE_KEY,pct_change_l1) %>%
arrange(.,start_date) %>%
knitr::kable(., align = "lccrr",format.args = list(big.mark = ","))
| 2020-04-01 |
First contacts (<18) |
-16.342322 |
| 2020-05-01 |
First contacts (<18) |
-21.321577 |
| 2020-06-01 |
First contacts (<18) |
-1.012012 |
| 2020-07-01 |
First contacts (<18) |
-1.258982 |
| 2020-08-01 |
First contacts (<18) |
7.380612 |
| 2020-09-01 |
First contacts (<18) |
8.388065 |
| 2020-10-01 |
First contacts (<18) |
4.367028 |
| 2020-11-01 |
First contacts (<18) |
11.677623 |
| 2020-12-01 |
First contacts (<18) |
17.935392 |
| 2021-01-01 |
First contacts (<18) |
-10.543266 |
| 2021-02-01 |
First contacts (<18) |
-7.586273 |
| 2021-03-01 |
First contacts (<18) |
14.916109 |
| 2021-04-01 |
First contacts (<18) |
33.501364 |
| 2021-05-01 |
First contacts (<18) |
60.596146 |
| 2021-06-01 |
First contacts (<18) |
36.164866 |
| 2021-07-01 |
First contacts (<18) |
16.332180 |
| 2021-08-01 |
First contacts (<18) |
10.370181 |
| 2021-09-01 |
First contacts (<18) |
12.933646 |
Attended contacts (<18)
- Measure code: MHS30d
- Measure description: Attended contacts in the RP, aged 0-18
- Source: NHS England, Monthly MHSDS Statistics, Metadata
Raw time series
#Data
CAMHS_data_cyp30d <- CAMHS_data %>%
filter(.,MEASURE_ID=="MHS30d")
CAMHS_reldata_cyp30d <- CAMHS_yearly_changes %>%
filter(.,MEASURE_ID=="MHS30d")
#Time series chart
CAMHS_raw_chart_cyp30d <- CAMHS_data_cyp30d %>%
ggplot(., aes(x=start_date, y=MEASURE_VALUE, group= MEASURE_KEY)) +
geom_line(aes(color= MEASURE_KEY),
size=1) +
scale_x_date(date_labels = "%b %Y",date_breaks = "3 months") +
scale_y_continuous(labels = scales::comma) +
facet_wrap(~timing, scales = "free_x") +
theme_ipsum() +
xlab("") +
ylab("") +
labs(col="") +
scale_color_brewer(palette = "Set1") +
theme(legend.position="bottom",
panel.border = element_blank(),
strip.text = element_text(size=8),
text = element_text(size = 8),
legend.title=element_text(size=8),
legend.text=element_text(size=8),
axis.text = element_text(size = 8),
axis.text.y = element_text(size = 8),
axis.text.x = element_text(angle = 45, hjust = 1,size = 8),
axis.title.x = element_text(margin = unit(c(3, 0, 0, 0), "mm"),size = 8),
axis.title.y = element_text(size = 8))
ggplotly(CAMHS_raw_chart_cyp30d)
#Underlying data
CAMHS_data_cyp30d %>%
select(.,start_date,MEASURE_KEY,MEASURE_VALUE) %>%
arrange(.,start_date) %>%
knitr::kable(., align = "lccrr",format.args = list(big.mark = ","))
| 2019-04-01 |
Attended contacts (<18) |
307,328 |
| 2019-05-01 |
Attended contacts (<18) |
346,997 |
| 2019-06-01 |
Attended contacts (<18) |
337,476 |
| 2019-07-01 |
Attended contacts (<18) |
363,594 |
| 2019-08-01 |
Attended contacts (<18) |
274,323 |
| 2019-09-01 |
Attended contacts (<18) |
335,775 |
| 2019-10-01 |
Attended contacts (<18) |
388,130 |
| 2019-11-01 |
Attended contacts (<18) |
383,387 |
| 2019-12-01 |
Attended contacts (<18) |
305,574 |
| 2020-01-01 |
Attended contacts (<18) |
402,520 |
| 2020-02-01 |
Attended contacts (<18) |
361,178 |
| 2020-03-01 |
Attended contacts (<18) |
384,011 |
| 2020-04-01 |
Attended contacts (<18) |
365,212 |
| 2020-05-01 |
Attended contacts (<18) |
360,525 |
| 2020-06-01 |
Attended contacts (<18) |
424,827 |
| 2020-07-01 |
Attended contacts (<18) |
425,810 |
| 2020-08-01 |
Attended contacts (<18) |
336,675 |
| 2020-09-01 |
Attended contacts (<18) |
419,474 |
| 2020-10-01 |
Attended contacts (<18) |
435,613 |
| 2020-11-01 |
Attended contacts (<18) |
473,103 |
| 2020-12-01 |
Attended contacts (<18) |
397,443 |
| 2021-01-01 |
Attended contacts (<18) |
426,820 |
| 2021-02-01 |
Attended contacts (<18) |
412,003 |
| 2021-03-01 |
Attended contacts (<18) |
488,234 |
| 2021-04-01 |
Attended contacts (<18) |
437,736 |
| 2021-05-01 |
Attended contacts (<18) |
463,893 |
| 2021-06-01 |
Attended contacts (<18) |
469,830 |
| 2021-07-01 |
Attended contacts (<18) |
443,801 |
| 2021-08-01 |
Attended contacts (<18) |
350,766 |
| 2021-09-01 |
Attended contacts (<18) |
437,555 |
Monthly average, per year
#Average per calendar year
CAMHS_data_cyp30d %>%
mutate(.,year=lubridate::year(start_date)) %>%
group_by(MEASURE_ID,MEASURE_KEY,year) %>%
summarise(average=mean(MEASURE_VALUE,na.rm = TRUE),
months_included= n()) %>%
ungroup() %>%
filter(.,months_included==12) %>%
knitr::kable(., align = "lccrr")
| MHS30d |
Attended contacts (<18) |
2020 |
398865.9 |
12 |
Relative changes compared to last year
#Relative changes chart
CAMHS_changes_chart_cyp30d <- CAMHS_reldata_cyp30d %>%
ggplot(., aes(x=start_date, y=pct_change_l1, group= MEASURE_KEY)) +
facet_wrap(~timing, scales = "free_x") +
geom_line(aes(color= MEASURE_KEY),size=1) +
geom_hline(yintercept=0, linetype="dashed", color = "red") +
scale_x_date(date_labels = "%b %Y",date_breaks = "1 month") +
theme_ipsum() +
xlab("") +
ylab("% change") +
labs(col="") +
scale_color_manual(values=c("Open referrals" = "aquamarine4",
"People in contact" = "tomato3",
"First contacts (<18)" = "olivedrab4",
"Attended contacts (<18)" = "violetred",
"New referrals (<18)" = "magenta1")) +
theme(legend.position="bottom",
panel.border = element_blank(),
strip.text = element_text(size=8),
text = element_text(size = 8),
legend.title=element_text(size=8),
legend.text=element_text(size=8),
axis.text = element_text(size = 8),
axis.text.y = element_text(size = 8),
axis.text.x = element_text(angle = 45, hjust = 1,size = 8),
axis.title.x = element_text(margin = unit(c(3, 0, 0, 0), "mm"),size = 8),
axis.title.y = element_text(size = 8))
ggplotly(CAMHS_changes_chart_cyp30d)
#Underlying data
CAMHS_reldata_cyp30d %>%
select(.,start_date,MEASURE_KEY,pct_change_l1) %>%
arrange(.,start_date) %>%
knitr::kable(., align = "lccrr",format.args = list(big.mark = ","))
| 2020-04-01 |
Attended contacts (<18) |
18.834600 |
| 2020-05-01 |
Attended contacts (<18) |
3.898593 |
| 2020-06-01 |
Attended contacts (<18) |
25.883618 |
| 2020-07-01 |
Attended contacts (<18) |
17.111393 |
| 2020-08-01 |
Attended contacts (<18) |
22.729410 |
| 2020-09-01 |
Attended contacts (<18) |
24.927109 |
| 2020-10-01 |
Attended contacts (<18) |
12.233788 |
| 2020-11-01 |
Attended contacts (<18) |
23.400898 |
| 2020-12-01 |
Attended contacts (<18) |
30.064403 |
| 2021-01-01 |
Attended contacts (<18) |
6.036967 |
| 2021-02-01 |
Attended contacts (<18) |
14.072009 |
| 2021-03-01 |
Attended contacts (<18) |
27.140629 |
| 2021-04-01 |
Attended contacts (<18) |
19.858055 |
| 2021-05-01 |
Attended contacts (<18) |
28.671521 |
| 2021-06-01 |
Attended contacts (<18) |
10.593253 |
| 2021-07-01 |
Attended contacts (<18) |
4.225124 |
| 2021-08-01 |
Attended contacts (<18) |
4.185342 |
| 2021-09-01 |
Attended contacts (<18) |
4.310398 |
Open referrals
- Measure code: CYP23
- Measure description: Open referrals (children’s and young people’s mental health services) at end of the reporting period
- Source: NHS England, Monthly MHSDS Statistics, Metadata
Raw time series
#Data
CAMHS_data_cyp23 <- CAMHS_data %>%
filter(.,MEASURE_ID=="CYP23")
CAMHS_reldata_cyp23 <- CAMHS_yearly_changes %>%
filter(.,MEASURE_ID=="CYP23")
#Time series chart
CAMHS_raw_chart_cyp23 <- CAMHS_data_cyp23 %>%
ggplot(., aes(x=start_date, y=MEASURE_VALUE, group= MEASURE_KEY)) +
geom_line(aes(color= MEASURE_KEY),
size=1) +
scale_x_date(date_labels = "%b %Y",date_breaks = "3 months") +
scale_y_continuous(labels = scales::comma) +
facet_wrap(~timing, scales = "free_x") +
theme_ipsum() +
xlab("") +
ylab("") +
labs(col="") +
scale_color_brewer(palette = "Set1") +
theme(legend.position="bottom",
panel.border = element_blank(),
strip.text = element_text(size=8),
text = element_text(size = 8),
legend.title=element_text(size=8),
legend.text=element_text(size=8),
axis.text = element_text(size = 8),
axis.text.y = element_text(size = 8),
axis.text.x = element_text(angle = 45, hjust = 1,size = 8),
axis.title.x = element_text(margin = unit(c(3, 0, 0, 0), "mm"),size = 8),
axis.title.y = element_text(size = 8))
ggplotly(CAMHS_raw_chart_cyp23)
#Underlying data
CAMHS_data_cyp23 %>%
select(.,start_date,MEASURE_KEY,MEASURE_VALUE) %>%
arrange(.,start_date) %>%
knitr::kable(., align = "lccrr",format.args = list(big.mark = ","))
| 2018-05-01 |
Open referrals |
247,499 |
| 2018-06-01 |
Open referrals |
251,573 |
| 2018-07-01 |
Open referrals |
243,916 |
| 2018-08-01 |
Open referrals |
238,803 |
| 2018-09-01 |
Open referrals |
245,003 |
| 2018-10-01 |
Open referrals |
255,855 |
| 2018-11-01 |
Open referrals |
252,726 |
| 2018-12-01 |
Open referrals |
256,644 |
| 2019-01-01 |
Open referrals |
258,525 |
| 2019-02-01 |
Open referrals |
264,305 |
| 2019-03-01 |
Open referrals |
272,605 |
| 2019-04-01 |
Open referrals |
248,038 |
| 2019-05-01 |
Open referrals |
260,485 |
| 2019-06-01 |
Open referrals |
255,950 |
| 2019-07-01 |
Open referrals |
257,152 |
| 2019-08-01 |
Open referrals |
248,313 |
| 2019-09-01 |
Open referrals |
251,483 |
| 2019-10-01 |
Open referrals |
256,252 |
| 2019-11-01 |
Open referrals |
262,299 |
| 2019-12-01 |
Open referrals |
261,939 |
| 2020-01-01 |
Open referrals |
268,184 |
| 2020-02-01 |
Open referrals |
272,482 |
| 2020-03-01 |
Open referrals |
267,871 |
| 2020-04-01 |
Open referrals |
307,837 |
| 2020-05-01 |
Open referrals |
302,241 |
| 2020-06-01 |
Open referrals |
301,012 |
| 2020-07-01 |
Open referrals |
304,491 |
| 2020-08-01 |
Open referrals |
300,469 |
| 2020-09-01 |
Open referrals |
318,375 |
| 2020-10-01 |
Open referrals |
329,392 |
| 2020-11-01 |
Open referrals |
344,178 |
| 2020-12-01 |
Open referrals |
345,569 |
| 2021-01-01 |
Open referrals |
340,421 |
| 2021-02-01 |
Open referrals |
340,218 |
| 2021-03-01 |
Open referrals |
352,551 |
| 2021-04-01 |
Open referrals |
358,282 |
| 2021-05-01 |
Open referrals |
374,401 |
| 2021-06-01 |
Open referrals |
379,079 |
| 2021-07-01 |
Open referrals |
380,738 |
| 2021-08-01 |
Open referrals |
368,610 |
| 2021-09-01 |
Open referrals |
374,946 |
Monthly average, per year
#Average per calendar year
CAMHS_data_cyp23 %>%
mutate(.,year=lubridate::year(start_date)) %>%
group_by(MEASURE_ID,MEASURE_KEY,year) %>%
summarise(average=mean(MEASURE_VALUE,na.rm = TRUE),
months_included= n()) %>%
ungroup() %>%
filter(.,months_included==12) %>%
knitr::kable(., align = "lccrr")
| CYP23 |
Open referrals |
2019 |
258112.2 |
12 |
| CYP23 |
Open referrals |
2020 |
305175.1 |
12 |
Relative changes compared to last year
#Relative changes chart
CAMHS_changes_chart_cyp23 <- CAMHS_reldata_cyp23 %>%
ggplot(., aes(x=start_date, y=pct_change_l1, group= MEASURE_KEY)) +
facet_wrap(~timing, scales = "free_x") +
geom_line(aes(color= MEASURE_KEY),size=1) +
geom_hline(yintercept=0, linetype="dashed", color = "red") +
scale_x_date(date_labels = "%b %Y",date_breaks = "1 month") +
theme_ipsum() +
xlab("") +
ylab("% change") +
labs(col="") +
scale_color_manual(values=c("Open referrals" = "aquamarine4",
"People in contact" = "tomato3",
"First contacts (<18)" = "olivedrab4",
"Attended contacts (<18)" = "violetred",
"New referrals (<18)" = "magenta1")) +
theme(legend.position="bottom",
panel.border = element_blank(),
strip.text = element_text(size=8),
text = element_text(size = 8),
legend.title=element_text(size=8),
legend.text=element_text(size=8),
axis.text = element_text(size = 8),
axis.text.y = element_text(size = 8),
axis.text.x = element_text(angle = 45, hjust = 1,size = 8),
axis.title.x = element_text(margin = unit(c(3, 0, 0, 0), "mm"),size = 8),
axis.title.y = element_text(size = 8))
ggplotly(CAMHS_changes_chart_cyp23)
#Underlying data
CAMHS_reldata_cyp23 %>%
select(.,start_date,MEASURE_KEY,pct_change_l1) %>%
arrange(.,start_date) %>%
knitr::kable(., align = "lccrr",format.args = list(big.mark = ","))
| 2019-05-01 |
Open referrals |
5.246890 |
| 2019-06-01 |
Open referrals |
1.739853 |
| 2019-07-01 |
Open referrals |
5.426458 |
| 2019-08-01 |
Open referrals |
3.982362 |
| 2019-09-01 |
Open referrals |
2.644866 |
| 2019-10-01 |
Open referrals |
0.155166 |
| 2019-11-01 |
Open referrals |
3.787897 |
| 2019-12-01 |
Open referrals |
2.063169 |
| 2020-01-01 |
Open referrals |
3.736196 |
| 2020-02-01 |
Open referrals |
3.093774 |
| 2020-03-01 |
Open referrals |
-1.736579 |
| 2020-04-01 |
Open referrals |
24.108806 |
| 2020-05-01 |
Open referrals |
16.030098 |
| 2020-06-01 |
Open referrals |
17.605782 |
| 2020-07-01 |
Open referrals |
18.408957 |
| 2020-08-01 |
Open referrals |
21.004136 |
| 2020-09-01 |
Open referrals |
26.599015 |
| 2020-10-01 |
Open referrals |
28.542216 |
| 2020-11-01 |
Open referrals |
31.215902 |
| 2020-12-01 |
Open referrals |
31.927281 |
| 2021-01-01 |
Open referrals |
26.935611 |
| 2021-02-01 |
Open referrals |
24.858890 |
| 2021-03-01 |
Open referrals |
31.612231 |
| 2021-04-01 |
Open referrals |
16.386919 |
| 2021-05-01 |
Open referrals |
23.874987 |
| 2021-06-01 |
Open referrals |
25.934846 |
| 2021-07-01 |
Open referrals |
25.040806 |
| 2021-08-01 |
Open referrals |
22.678213 |
| 2021-09-01 |
Open referrals |
17.768669 |
People with eating disorders being seen within target times (<18)
Measure code: ED86e
Measure description: Proportion of referrals with eating disorders categorized as urgent cases entering treatment within one week in RP, aged 0-18
Source: NHS England, Monthly MHSDS Statistics, Metadata
Measure code: ED87e
Measure description: Proportion of referrals with eating disorders categorized as routine cases entering treatment within four weeks in RP, aged 0-18
Source: NHS England, Monthly MHSDS Statistics, Metadata
#Eating disorders data
target_time_ed_data_new <- MHSDS_main_pooled_dashboard %>%
filter(.,PRIMARY_LEVEL_DESCRIPTION=="England",
MEASURE_ID %in% c("ED86e","ED87e")) %>%
select(.,start_date,end_date,PRIMARY_LEVEL_DESCRIPTION,MEASURE_ID,MEASURE_VALUE)
target_time_ed_data <- MHSDS_ED_pooled_dashboard %>%
filter(.,PRIMARY_LEVEL_DESCRIPTION=="England",
MEASURE_ID %in% c("ED86e","ED87e")) %>%
select(.,start_date,end_date,PRIMARY_LEVEL_DESCRIPTION,MEASURE_ID,MEASURE_VALUE) %>%
plyr::rbind.fill(.,target_time_ed_data_new) %>%
mutate(.,timing=ifelse(end_date<ymd("2020-04-01"),"Pre-COVID","Post-COVID")) %>%
mutate(.,timing=fct_relevel(timing, c("Pre-COVID","Post-COVID"))) %>%
mutate(.,MEASURE_VALUE=as.numeric(MEASURE_VALUE),
Type=case_when(MEASURE_ID=="ED86e" ~ "urgent",
MEASURE_ID=="ED87e" ~ "non urgent",
TRUE ~ "NA"))
#Eating disorders chart
target_time_ed_chart <- target_time_ed_data %>%
ggplot(., aes(x=end_date, y=MEASURE_VALUE, group=Type)) +
geom_line(aes(color=Type),size=1) +
scale_x_date(date_labels = "%b %Y",date_breaks = "1 month") +
scale_y_continuous(labels = scales::comma) +
facet_wrap(~timing, scales = "free_x") +
theme_ipsum() +
xlab("") +
ylab("") +
labs(col="", title="") +
scale_colour_manual(values=
c("urgent" = "brown", "non urgent" = "darkseagreen4")) +
theme(legend.position="bottom",
panel.border = element_blank(),
strip.text = element_text(size=8),
text = element_text(size = 8),
legend.title=element_text(size=8),
legend.text=element_text(size=8),
axis.text = element_text(size = 8),
axis.text.y = element_text(size = 8),
axis.text.x = element_text(angle = 45, hjust = 1,size = 8),
axis.title.x = element_text(margin = unit(c(3, 0, 0, 0), "mm"),size = 8),
axis.title.y = element_text(size = 8))
ggplotly(target_time_ed_chart)
Health Education England data on workforce (compared to activity levels from NHS England)
- Source of staff numbers is Health Education England report
#NHS Digital on people in contact with CAMHS service
CAMHS_contacts <- MHSDS_main_pooled_dashboard %>%
filter(.,PRIMARY_LEVEL_DESCRIPTION=="England",
MEASURE_ID=="CYP01") %>%
select(.,start_date,MEASURE_VALUE) %>%
mutate(.,date_ymd=lubridate::ymd(start_date)) %>%
mutate(.,date_ymd=floor_date(date_ymd, "month"),
measure="People in contact CAMHS",
MEASURE_VALUE=as.numeric(MEASURE_VALUE)) %>%
select(.,-"start_date") %>%
arrange(.,date_ymd)
#Turn into indexed data
CAMHS_contacts_index <- CAMHS_contacts %>%
mutate(.,MEASURE_VALUE_MA=zoo::rollmean(MEASURE_VALUE,k=7,fill=NA)) %>% #Use a moving average to compute the mean
mutate(.,Jan2019=filter(.,date_ymd=="2019-01-01")$MEASURE_VALUE_MA) %>%
filter(.,date_ymd>=ymd("2019-01-01"),!is.na(MEASURE_VALUE_MA)) %>%
mutate(.,index=MEASURE_VALUE_MA/Jan2019*100)
#HEE data (copied over from report)
HEE_staff_index <- data.frame(measure="CYP MH staff",
date_ymd=as.Date(c("2019-01-01","2021-04-01")),
MEASURE_VALUE=as.numeric(c("14857","20626"))) %>%
mutate(.,Jan2019=filter(.,date_ymd=="2019-01-01")$MEASURE_VALUE) %>%
mutate(.,index=MEASURE_VALUE/Jan2019*100)
#Append two sources together
CAMHS_and_HEE_staff <- plyr::rbind.fill(CAMHS_contacts_index,HEE_staff_index)
#Show data
CAMHS_and_HEE_staff %>%
knitr::kable(., align = "lccrr")
| 229217 |
2019-01-01 |
People in contact CAMHS |
228988.6 |
228988.6 |
100.00000 |
| 233831 |
2019-02-01 |
People in contact CAMHS |
229359.7 |
228988.6 |
100.16208 |
| 241926 |
2019-03-01 |
People in contact CAMHS |
229607.7 |
228988.6 |
100.27038 |
| 218678 |
2019-04-01 |
People in contact CAMHS |
229460.3 |
228988.6 |
100.20600 |
| 230443 |
2019-05-01 |
People in contact CAMHS |
227975.9 |
228988.6 |
99.55774 |
| 225480 |
2019-06-01 |
People in contact CAMHS |
226204.0 |
228988.6 |
98.78397 |
| 226647 |
2019-07-01 |
People in contact CAMHS |
223858.4 |
228988.6 |
97.75965 |
| 218826 |
2019-08-01 |
People in contact CAMHS |
225581.4 |
228988.6 |
98.51209 |
| 221428 |
2019-09-01 |
People in contact CAMHS |
225669.0 |
228988.6 |
98.55033 |
| 225507 |
2019-10-01 |
People in contact CAMHS |
227228.4 |
228988.6 |
99.23134 |
| 230739 |
2019-11-01 |
People in contact CAMHS |
229193.3 |
228988.6 |
100.08940 |
| 231056 |
2019-12-01 |
People in contact CAMHS |
231802.1 |
228988.6 |
101.22870 |
| 236396 |
2020-01-01 |
People in contact CAMHS |
240340.9 |
228988.6 |
104.95758 |
| 240401 |
2020-02-01 |
People in contact CAMHS |
247226.4 |
228988.6 |
107.96453 |
| 237088 |
2020-03-01 |
People in contact CAMHS |
253196.4 |
228988.6 |
110.57164 |
| 281199 |
2020-04-01 |
People in contact CAMHS |
259536.9 |
228988.6 |
113.34053 |
| 273706 |
2020-05-01 |
People in contact CAMHS |
264546.3 |
228988.6 |
115.52816 |
| 272529 |
2020-06-01 |
People in contact CAMHS |
271186.1 |
228988.6 |
118.42781 |
| 275439 |
2020-07-01 |
People in contact CAMHS |
279661.3 |
228988.6 |
122.12893 |
| 271462 |
2020-08-01 |
People in contact CAMHS |
283677.3 |
228988.6 |
123.88273 |
| 286880 |
2020-09-01 |
People in contact CAMHS |
289022.0 |
228988.6 |
126.21678 |
| 296414 |
2020-10-01 |
People in contact CAMHS |
293994.3 |
228988.6 |
128.38819 |
| 309311 |
2020-11-01 |
People in contact CAMHS |
298502.6 |
228988.6 |
130.35697 |
| 311119 |
2020-12-01 |
People in contact CAMHS |
305128.7 |
228988.6 |
133.25063 |
| 307335 |
2021-01-01 |
People in contact CAMHS |
310323.0 |
228988.6 |
135.51899 |
| 306997 |
2021-02-01 |
People in contact CAMHS |
316181.9 |
228988.6 |
138.07757 |
| 317845 |
2021-03-01 |
People in contact CAMHS |
320665.1 |
228988.6 |
140.03544 |
| 323240 |
2021-04-01 |
People in contact CAMHS |
325157.4 |
228988.6 |
141.99723 |
| 337426 |
2021-05-01 |
People in contact CAMHS |
328668.4 |
228988.6 |
143.53049 |
| 340694 |
2021-06-01 |
People in contact CAMHS |
332966.0 |
228988.6 |
145.40726 |
| 14857 |
2019-01-01 |
CYP MH staff |
NA |
14857.0 |
100.00000 |
| 20626 |
2021-04-01 |
CYP MH staff |
NA |
14857.0 |
138.83018 |
NHS England data on workforce (child and adolescent psychiatry only)
#NHS data
NHS_workforce_doctors %>%
mutate(.,date_ymd=lubridate::ymd(Date)) %>%
mutate(.,date_ymd=floor_date(date_ymd, "month"),
measure="FTE doctors") %>%
rename(.,MEASURE_VALUE=FTE) %>%
filter(Specialty %in% c("Child and adolescent psychiatry")) %>%
group_by(date_ymd,measure,Specialty) %>%
summarise(MEASURE_VALUE=sum(MEASURE_VALUE,na.rm=TRUE)) %>% #Aggregate over categories
ungroup() %>%
filter(., date_ymd %in% c(ymd("2019-01-01"),ymd("2021-04-01"))) %>%
pivot_wider(
names_from = date_ymd,
names_sep = ".",
values_from = MEASURE_VALUE
) %>%
mutate(.,pct_change=(`2021-04-01`-`2019-01-01`)/`2019-01-01`*100) %>%
knitr::kable(., align = "lccrr")
| FTE doctors |
Child and adolescent psychiatry |
981.6823 |
1064.256 |
8.411452 |
#Latest data on consultants
NHS_workforce_doctors %>%
mutate(.,date_ymd=lubridate::ymd(Date)) %>%
mutate(.,date_ymd=floor_date(date_ymd, "month"),
measure="FTE doctors") %>%
rename(.,MEASURE_VALUE=FTE) %>%
filter(., date_ymd %in% c(ymd("2021-05-01"))) %>%
filter(Specialty %in% c("Child and adolescent psychiatry")) %>%
select(.,-"Date") %>%
knitr::kable(., align = "lccrr")
| Consultant |
1 |
Psychiatry group |
Child and adolescent psychiatry |
626.5470 |
2021-05-01 |
FTE doctors |
| Associate Specialist |
2 |
Psychiatry group |
Child and adolescent psychiatry |
13.3725 |
2021-05-01 |
FTE doctors |
| Specialty Doctor |
3 |
Psychiatry group |
Child and adolescent psychiatry |
100.9210 |
2021-05-01 |
FTE doctors |
| Staff Grade |
4 |
Psychiatry group |
Child and adolescent psychiatry |
3.5000 |
2021-05-01 |
FTE doctors |
| Specialty Registrar |
5 |
Psychiatry group |
Child and adolescent psychiatry |
144.8688 |
2021-05-01 |
FTE doctors |
| Core Training |
6 |
Psychiatry group |
Child and adolescent psychiatry |
142.1062 |
2021-05-01 |
FTE doctors |
| Foundation Doctor Year 2 |
7 |
Psychiatry group |
Child and adolescent psychiatry |
10.0000 |
2021-05-01 |
FTE doctors |
| Foundation Doctor Year 1 |
8 |
Psychiatry group |
Child and adolescent psychiatry |
10.0000 |
2021-05-01 |
FTE doctors |